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2021,30(8):1-13, DOI: 10.15888/j.cnki.csa.008014
Abstract:
With the increasing complexity of emergencies related to the community correction object, the single fixed plan from the existing emergency plan database is unable to develop intelligent emergency response plans for different abnormal situations through dynamic data injection, which can hardly meet the demands of dynamic emergency generation. To improve the supervision quality and the informational management level of community correction object, we adopt the joint mining technology of multi-source heterogeneous data, in view of multi-source heterogeneity, complex association and dynamic evolution of abnormal situation data. On this basis, we build our judicial Knowledge Graph (KGjudicial) and crime Event Logic Graph (ELGcrime), providing data basis and auxiliary decision support for the dynamic generation of intelligent emergency plans. In addition, considering the actual business requirements for cross-regional multi-sectoral emergency coordination, we explore the multi-department information alignment method and the dynamic injection mechanism of emergency response plans. We propose the fusion technology of multiple-department emergency response plans based on our KGjudicial and ELGcrime to realize the cross-regional joint law enforcement of judicial administration departments and improve the supervision quality, while saving the management cost of community correction object. We provide technical support for the emergency response of multiple departments of judicial administration, contributing to the social security and stability.
With the increasing complexity of emergencies related to the community correction object, the single fixed plan from the existing emergency plan database is unable to develop intelligent emergency response plans for different abnormal situations through dynamic data injection, which can hardly meet the demands of dynamic emergency generation. To improve the supervision quality and the informational management level of community correction object, we adopt the joint mining technology of multi-source heterogeneous data, in view of multi-source heterogeneity, complex association and dynamic evolution of abnormal situation data. On this basis, we build our judicial Knowledge Graph (KGjudicial) and crime Event Logic Graph (ELGcrime), providing data basis and auxiliary decision support for the dynamic generation of intelligent emergency plans. In addition, considering the actual business requirements for cross-regional multi-sectoral emergency coordination, we explore the multi-department information alignment method and the dynamic injection mechanism of emergency response plans. We propose the fusion technology of multiple-department emergency response plans based on our KGjudicial and ELGcrime to realize the cross-regional joint law enforcement of judicial administration departments and improve the supervision quality, while saving the management cost of community correction object. We provide technical support for the emergency response of multiple departments of judicial administration, contributing to the social security and stability.
2021,30(8):14-21, DOI: 10.15888/j.cnki.csa.008003
Abstract:
This study summarizes the current research on semantic-based video retrieval to help future researchers understand the technologies available in this field, and video retrieval systems are created to find the video that users want to query in a large number of video data collections on the Internet or in databases. This study introduces and discusses the semantic-based video retrieval process and also summarizes the relevant techniques to solve the main problem of a semantic gap in this process. The semantic gap is induced by the difference between the low-level features extracted from video content and the user’s cognition of these features in the real world. It is a highly concerned research topic to transform the low-level features of video content into high-level semantic concepts.
This study summarizes the current research on semantic-based video retrieval to help future researchers understand the technologies available in this field, and video retrieval systems are created to find the video that users want to query in a large number of video data collections on the Internet or in databases. This study introduces and discusses the semantic-based video retrieval process and also summarizes the relevant techniques to solve the main problem of a semantic gap in this process. The semantic gap is induced by the difference between the low-level features extracted from video content and the user’s cognition of these features in the real world. It is a highly concerned research topic to transform the low-level features of video content into high-level semantic concepts.
2021,30(8):22-30, DOI: 10.15888/j.cnki.csa.008110
Abstract:
In recent years, the quantitative investment models based on artificial intelligence algorithms have been emerging in the field of quantitative finance. These models attempt to model the financial time series through artificial intelligence methods, thereby forecasting data and developing an investment strategy. Regarding the unreliable prediction of the traditional Long Short Term Memory (LSTM) model for financial time series, we propose an improved LSTM model. The attention mechanism is added into the LSTM layer to enhance the forecasting performance of the neural network, and the Genetic Algorithm (GA) is used to optimize parameters, thus improving the model’s generalization ability. The data of China’s stock indexes and futures from the January 2019 to May 2020 is selected for the comparative experiments with state-of-the-art algorithms. The results show that the improved model performs better than other models in every indicators, proving the effect application of the model to future investment.
In recent years, the quantitative investment models based on artificial intelligence algorithms have been emerging in the field of quantitative finance. These models attempt to model the financial time series through artificial intelligence methods, thereby forecasting data and developing an investment strategy. Regarding the unreliable prediction of the traditional Long Short Term Memory (LSTM) model for financial time series, we propose an improved LSTM model. The attention mechanism is added into the LSTM layer to enhance the forecasting performance of the neural network, and the Genetic Algorithm (GA) is used to optimize parameters, thus improving the model’s generalization ability. The data of China’s stock indexes and futures from the January 2019 to May 2020 is selected for the comparative experiments with state-of-the-art algorithms. The results show that the improved model performs better than other models in every indicators, proving the effect application of the model to future investment.
2021,30(8):31-39, DOI: 10.15888/j.cnki.csa.008017
Abstract:
Building energy-saving control is a multi-objective optimization problem considering the comfort demand. However, for the new buildings lacking operation data, it is a real conundrum to control the Heating, Ventilation and Air-Conditioning (HVAC) system to achieve both comfort and energy-saving. Aiming at this problem, this study first builds the space model of new buildings and then carries out simulation of energy consumption on the model. On this basis, it puts forward a fuzzy control algorithm based on thermal comfort of personnel to determine the optimal operation interval. Therefore, longer days of thermal comfort are enabled under the condition of lower energy consumption, achieving the goal of both energy saving and comfort. The energy-saving control based on the thermal comfort of personnel can promote the green operation of HVAC systems in buildings.
Building energy-saving control is a multi-objective optimization problem considering the comfort demand. However, for the new buildings lacking operation data, it is a real conundrum to control the Heating, Ventilation and Air-Conditioning (HVAC) system to achieve both comfort and energy-saving. Aiming at this problem, this study first builds the space model of new buildings and then carries out simulation of energy consumption on the model. On this basis, it puts forward a fuzzy control algorithm based on thermal comfort of personnel to determine the optimal operation interval. Therefore, longer days of thermal comfort are enabled under the condition of lower energy consumption, achieving the goal of both energy saving and comfort. The energy-saving control based on the thermal comfort of personnel can promote the green operation of HVAC systems in buildings.
2021,30(8):40-49, DOI: 10.15888/j.cnki.csa.008018
Abstract:
The study of crystal structure is the basis for studying the physical and chemical properties of solid materials, and the screening of crystal structure is usually based on the principle of least energy. The use of density functional theory to calculate the structure energy requires a lot of computing resources and service time. For this reason, this research proposes a deep learning method for material structure prediction to speed up the prediction of material crystal structure. This work systematically studied and analyzed the data set optimization, training method, algorithm optimization, and so on. The network parameters and optimized algorithm of deep learning for crystal structure prediction are confirmed and coded. The optimized deep learning method is used to find out stable structure of Silicon, titanium dioxide, and perovskite CaTiO3, the predicted structures are well agreement with the experimental results.
The study of crystal structure is the basis for studying the physical and chemical properties of solid materials, and the screening of crystal structure is usually based on the principle of least energy. The use of density functional theory to calculate the structure energy requires a lot of computing resources and service time. For this reason, this research proposes a deep learning method for material structure prediction to speed up the prediction of material crystal structure. This work systematically studied and analyzed the data set optimization, training method, algorithm optimization, and so on. The network parameters and optimized algorithm of deep learning for crystal structure prediction are confirmed and coded. The optimized deep learning method is used to find out stable structure of Silicon, titanium dioxide, and perovskite CaTiO3, the predicted structures are well agreement with the experimental results.
2021,30(8):50-59, DOI: 10.15888/j.cnki.csa.008083
Abstract:
To improve the racing performance of intelligent cars, this study introduces an intelligent racing car system based on IMXRT1021 with regard to selection of key components, design of hardware and circuit boards, and processing of sensor signals, as well as assembly, algorithms and control. This system consists of mechanical and hardware parts, PCB design, sensor signal processing, the recognition algorithm of racing track elements, control strategy and software design architecture. This study experimentally elaborates the recognition and control schemes of each racing elements. It compares the driving trajectories and absolute velocities of intelligent cars and analyzes the influence of different control algorithms on vital technical specifications such as finish time and stability. This design scheme shows its advantages in accurate control, sensitive steering and careful route planning, providing a sound reference for the students who are preparing for the four-wheel group in the National University Students Intelligent Car Race.
To improve the racing performance of intelligent cars, this study introduces an intelligent racing car system based on IMXRT1021 with regard to selection of key components, design of hardware and circuit boards, and processing of sensor signals, as well as assembly, algorithms and control. This system consists of mechanical and hardware parts, PCB design, sensor signal processing, the recognition algorithm of racing track elements, control strategy and software design architecture. This study experimentally elaborates the recognition and control schemes of each racing elements. It compares the driving trajectories and absolute velocities of intelligent cars and analyzes the influence of different control algorithms on vital technical specifications such as finish time and stability. This design scheme shows its advantages in accurate control, sensitive steering and careful route planning, providing a sound reference for the students who are preparing for the four-wheel group in the National University Students Intelligent Car Race.
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Available online: July 13, 2021 , DOI: 10.15888/j.cnki.csa.008280
Abstract:
With the continuous development of digital twin technology at this stage, research and applications surrounding digital twins have gradually become a hot spot. Because traditional automated driving test methods have various defects in terms of functionality, safety, and test cost, this article proposes a digital twin automatic driving test method based on the basic characteristics of the digital twin and the test method of autonomous driving. The method of constructing the driving test environment uses spatial coordinate mapping, collision detection model, and virtual scene registration to map the automatic driving information in the actual environment to the virtual scene. At the same time, the corresponding mixed reality automatic driving test model is constructed and passed the experiment. The collision test with interactive features of the mixed reality system is shown. The performance of the system at sampling frequencies of 50ms, 200ms and 1000ms is compared and analyzed. Experiments show that the algorithm in this paper has better operating frame rate characteristics at the sampling frequency of 200ms or above.
With the continuous development of digital twin technology at this stage, research and applications surrounding digital twins have gradually become a hot spot. Because traditional automated driving test methods have various defects in terms of functionality, safety, and test cost, this article proposes a digital twin automatic driving test method based on the basic characteristics of the digital twin and the test method of autonomous driving. The method of constructing the driving test environment uses spatial coordinate mapping, collision detection model, and virtual scene registration to map the automatic driving information in the actual environment to the virtual scene. At the same time, the corresponding mixed reality automatic driving test model is constructed and passed the experiment. The collision test with interactive features of the mixed reality system is shown. The performance of the system at sampling frequencies of 50ms, 200ms and 1000ms is compared and analyzed. Experiments show that the algorithm in this paper has better operating frame rate characteristics at the sampling frequency of 200ms or above.
Available online: June 23, 2021 , DOI: 10.15888/j.cnki.csa.008287
Abstract:
Soybeans include many varieties (cultivars) and their cultivars have very subtle differences in leaf patterns which makes it very tough to distinguish them from leaf features. Great progress has been made on using leaf image patterns for plant species recognition. However, as a general very fined-grained pattern recognition problem, soybean cultivar recognition has not yet received considerable attention. Traditional handcrafted leaf image analysis methods are limited to capture the subtle differences of leaf features among different cultivars. In this paper, we make the attempt of using deep learning to harvest discriminatory leaf features for soybean cultivar recognition. A novel deep learning model, named transformation attention network (TAN), is proposed in this work. It first focuses on extracting fine-grained leaf features via attention mechanism and then rectifies the leaf posture using affine transformations. We constructed a soybean leaf cultivar dataset which consists of 240 soybean cultivars with 10 samples per cultivar to examine the availability of cultivar information in leaf patterns and validate the effectiveness of the proposed deep learning model for soybean cultivar recognition. The encouraging experimental results confirm the effectiveness of leaf image patterns for distinguishing cultivars and demonstrate the better performance of the proposed method over the state-of-the-art handcrafted methods and deep learning methods for soybean cultivar recognition.
Soybeans include many varieties (cultivars) and their cultivars have very subtle differences in leaf patterns which makes it very tough to distinguish them from leaf features. Great progress has been made on using leaf image patterns for plant species recognition. However, as a general very fined-grained pattern recognition problem, soybean cultivar recognition has not yet received considerable attention. Traditional handcrafted leaf image analysis methods are limited to capture the subtle differences of leaf features among different cultivars. In this paper, we make the attempt of using deep learning to harvest discriminatory leaf features for soybean cultivar recognition. A novel deep learning model, named transformation attention network (TAN), is proposed in this work. It first focuses on extracting fine-grained leaf features via attention mechanism and then rectifies the leaf posture using affine transformations. We constructed a soybean leaf cultivar dataset which consists of 240 soybean cultivars with 10 samples per cultivar to examine the availability of cultivar information in leaf patterns and validate the effectiveness of the proposed deep learning model for soybean cultivar recognition. The encouraging experimental results confirm the effectiveness of leaf image patterns for distinguishing cultivars and demonstrate the better performance of the proposed method over the state-of-the-art handcrafted methods and deep learning methods for soybean cultivar recognition.
Abstract:
In order to analyze the research status, development trend and research hotspots in the field of source address verification in China, and sort out the development trend of source address verification research, so as to promote the further research on trusted transmission of national network data. This paper takes the papers and literatures based on source address verification in CNKI database as the research data source, applies bib-liometrics and scientific knowledge map, and uses CiteSpace as a visual tool to carry out information statistics, co-citation statistics and cluster analysis on the research samples, and draws the inter-annual variation map of the literature in this research field and the knowledge map of co-occurrence clustering and time-series dis-tribution, so as to make scientific analysis. The research shows that the research of source address verification in China tends to develop dynamically and the trend is stable and good; Core research strength: headed by Professor Wu Jianping, Jun Bi and Xu Wei as important research experts and headed by Tsinghua University, PLA Information Engineering University and Chinese Academy of Sciences as important research institutions; Next generation Internet and software-defined network are important emerging research hotspots, which reflect the future research direction and development trend of source address verification research.
In order to analyze the research status, development trend and research hotspots in the field of source address verification in China, and sort out the development trend of source address verification research, so as to promote the further research on trusted transmission of national network data. This paper takes the papers and literatures based on source address verification in CNKI database as the research data source, applies bib-liometrics and scientific knowledge map, and uses CiteSpace as a visual tool to carry out information statistics, co-citation statistics and cluster analysis on the research samples, and draws the inter-annual variation map of the literature in this research field and the knowledge map of co-occurrence clustering and time-series dis-tribution, so as to make scientific analysis. The research shows that the research of source address verification in China tends to develop dynamically and the trend is stable and good; Core research strength: headed by Professor Wu Jianping, Jun Bi and Xu Wei as important research experts and headed by Tsinghua University, PLA Information Engineering University and Chinese Academy of Sciences as important research institutions; Next generation Internet and software-defined network are important emerging research hotspots, which reflect the future research direction and development trend of source address verification research.
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本文详细讨论了VRML技术与其他数据访问技术相结合 ,实现对数据库实时交互的技术实现方法 ,并简要阐述了相关技术规范的语法结构和技术要求。所用技术手段安全可靠 ,具有良好的实际应用表现 ,便于系统移植。
本文详细讨论了VRML技术与其他数据访问技术相结合 ,实现对数据库实时交互的技术实现方法 ,并简要阐述了相关技术规范的语法结构和技术要求。所用技术手段安全可靠 ,具有良好的实际应用表现 ,便于系统移植。
Abstract:
本文介绍了作者近年来应用工具软件NU清除磁盘引导区和硬盘主引导区病毒、修复引导区损坏磁盘的 经验，经实践检验，简便有效。
本文介绍了作者近年来应用工具软件NU清除磁盘引导区和硬盘主引导区病毒、修复引导区损坏磁盘的 经验，经实践检验，简便有效。
Abstract:
本文简要介绍了海关EDI自动化通关系统的定义概况及重要意义，对该EDI应用系统下的业务运作模式所涉及的法律问题，采用EDIFACT国际标准问题、网络与软件技术问题，以及工程管理问题进行了结合实际的分析。
本文简要介绍了海关EDI自动化通关系统的定义概况及重要意义，对该EDI应用系统下的业务运作模式所涉及的法律问题，采用EDIFACT国际标准问题、网络与软件技术问题，以及工程管理问题进行了结合实际的分析。
Abstract:
在研究了目前主流的视频转码方案基础上,提出了一种分布式转码系统。系统采用HDFS(HadoopDistributed File System)进行视频存储,利用MapReduce 思想和FFMPEG 进行分布式转码。详细讨论了视频分布式存储时的分段策略,以及分段大小对存取时间的影响。同时,定义了视频存储和转换的元数据格式。提出了基于MapReduce 编程框架的分布式转码方案,即Mapper 端进行转码和Reducer 端进行视频合并。实验数据显示了转码时间随视频分段大小和转码机器数量不同而变化的趋势。结
在研究了目前主流的视频转码方案基础上,提出了一种分布式转码系统。系统采用HDFS(HadoopDistributed File System)进行视频存储,利用MapReduce 思想和FFMPEG 进行分布式转码。详细讨论了视频分布式存储时的分段策略,以及分段大小对存取时间的影响。同时,定义了视频存储和转换的元数据格式。提出了基于MapReduce 编程框架的分布式转码方案,即Mapper 端进行转码和Reducer 端进行视频合并。实验数据显示了转码时间随视频分段大小和转码机器数量不同而变化的趋势。结
Abstract:
随着Internet的迅速发展，网络资源越来越丰富，人们如何从网络上抽取信息也变得至关重要，尤其是占网络资源80%的Deep Web信息检索更是人们应该倍加关注的难点问题。为了更好的研究Deep Web爬虫技术，本文对有关Deep Web爬虫的内容进行了全面、详细地介绍。首先对Deep Web爬虫的定义及研究目标进行了阐述，接着介绍了近年来国内外关于Deep Web爬虫的研究进展，并对其加以分析。在此基础上展望了Deep Web爬虫的研究趋势，为下一步的研究奠定了基础。
随着Internet的迅速发展，网络资源越来越丰富，人们如何从网络上抽取信息也变得至关重要，尤其是占网络资源80%的Deep Web信息检索更是人们应该倍加关注的难点问题。为了更好的研究Deep Web爬虫技术，本文对有关Deep Web爬虫的内容进行了全面、详细地介绍。首先对Deep Web爬虫的定义及研究目标进行了阐述，接着介绍了近年来国内外关于Deep Web爬虫的研究进展，并对其加以分析。在此基础上展望了Deep Web爬虫的研究趋势，为下一步的研究奠定了基础。
2016,25(8):1-7, DOI: 10.15888/j.cnki.csa.005283
Abstract:
从2006年开始，深度神经网络在图像/语音识别、自动驾驶等大数据处理和人工智能领域中都取得了巨大成功，其中无监督学习方法作为深度神经网络中的预训练方法为深度神经网络的成功起到了非常重要的作用. 为此，对深度学习中的无监督学习方法进行了介绍和分析，主要总结了两类常用的无监督学习方法，即确定型的自编码方法和基于概率型受限玻尔兹曼机的对比散度等学习方法，并介绍了这两类方法在深度学习系统中的应用，最后对无监督学习面临的问题和挑战进行了总结和展望.
从2006年开始，深度神经网络在图像/语音识别、自动驾驶等大数据处理和人工智能领域中都取得了巨大成功，其中无监督学习方法作为深度神经网络中的预训练方法为深度神经网络的成功起到了非常重要的作用. 为此，对深度学习中的无监督学习方法进行了介绍和分析，主要总结了两类常用的无监督学习方法，即确定型的自编码方法和基于概率型受限玻尔兹曼机的对比散度等学习方法，并介绍了这两类方法在深度学习系统中的应用，最后对无监督学习面临的问题和挑战进行了总结和展望.
Abstract:
用较少的颜色来表示较大的色彩空间一直是人们研究的课题，本文详细讨论了半色调技术和抖动技术，并将它们扩展到实用的真彩色空间来讨论，并给出了实现的算法。
用较少的颜色来表示较大的色彩空间一直是人们研究的课题，本文详细讨论了半色调技术和抖动技术，并将它们扩展到实用的真彩色空间来讨论，并给出了实现的算法。
Abstract:
本文结合物流遗留系统的实际安全状态,分析了面向对象的编程思想在横切关注点和核心关注点处理上的不足,指出面向方面的编程思想解决方案对系统进行分离关注点处理的优势,并对面向方面的编程的一种具体实现AspectJ进行分析,提出了一种依据AspectJ对遗留物流系统进行IC卡安全进化的方法.
本文结合物流遗留系统的实际安全状态,分析了面向对象的编程思想在横切关注点和核心关注点处理上的不足,指出面向方面的编程思想解决方案对系统进行分离关注点处理的优势,并对面向方面的编程的一种具体实现AspectJ进行分析,提出了一种依据AspectJ对遗留物流系统进行IC卡安全进化的方法.
Abstract:
开放平台的核心问题是用户验证和授权问题,OAuth 是目前国际通用的授权方式,它的特点是不需要用户在第三方应用输入用户名及密码,就可以申请访问该用户的受保护资源。OAuth 最新版本是OAuth2.0,其认证与授权的流程更简单、更安全。研究了OAuth2.0 的工作原理,分析了刷新访问令牌的工作流程,并给出了OAuth2.0 服务器端的设计方案和具体的应用实例。
开放平台的核心问题是用户验证和授权问题,OAuth 是目前国际通用的授权方式,它的特点是不需要用户在第三方应用输入用户名及密码,就可以申请访问该用户的受保护资源。OAuth 最新版本是OAuth2.0,其认证与授权的流程更简单、更安全。研究了OAuth2.0 的工作原理,分析了刷新访问令牌的工作流程,并给出了OAuth2.0 服务器端的设计方案和具体的应用实例。
Abstract:
针对智能家居、环境监测等的实际要求，设计了一种远距离通讯的无线传感器节点。该系统采用集射频与控制器于一体的第二代片上系统CC2530 为核心模块，外接CC2591 射频前端功放模块；软件上基于ZigBee2006 协议栈，在ZStack 通用模块基础上实现应用层各项功能。介绍了基于ZigBee 协议构建无线数据采集网络，给出了传感器节点、协调器节点的硬件设计原理图及软件流程图。实验证明节点性能良好、通讯可靠,通讯距离较TI 第一代产品有明显增大。
针对智能家居、环境监测等的实际要求，设计了一种远距离通讯的无线传感器节点。该系统采用集射频与控制器于一体的第二代片上系统CC2530 为核心模块，外接CC2591 射频前端功放模块；软件上基于ZigBee2006 协议栈，在ZStack 通用模块基础上实现应用层各项功能。介绍了基于ZigBee 协议构建无线数据采集网络，给出了传感器节点、协调器节点的硬件设计原理图及软件流程图。实验证明节点性能良好、通讯可靠,通讯距离较TI 第一代产品有明显增大。
Abstract:
本文介绍了车辆监控系统的组成,研究了如何应用Rockwell GPS OEM板和WISMOQUIKQ2406B模块进行移动单元的软硬件设计,以及监控中心 GIS软件的设计.重点介绍嵌入TCP/IP协议处理的Q2406B模块如何通过AT指令接入Internet以及如何和监控中心传输TCP数据.
本文介绍了车辆监控系统的组成,研究了如何应用Rockwell GPS OEM板和WISMOQUIKQ2406B模块进行移动单元的软硬件设计,以及监控中心 GIS软件的设计.重点介绍嵌入TCP/IP协议处理的Q2406B模块如何通过AT指令接入Internet以及如何和监控中心传输TCP数据.
Abstract:
随着面向对象软件开发技术的广泛应用和软件测试自动化的要求，基于模型的软件测试逐渐得到了软件开发人员和软件测试人员的认可和接受。基于模型的软件测试是软件编码阶段的主要测试方法之一，具有测试效率高、排除逻辑复杂故障测试效果好等特点。但是误报、漏报和故障机理有待进一步研究。对主要的测试模型进行了分析和分类，同时，对故障密度等参数进行了初步的分析；最后，提出了一种基于模型的软件测试流程。
随着面向对象软件开发技术的广泛应用和软件测试自动化的要求，基于模型的软件测试逐渐得到了软件开发人员和软件测试人员的认可和接受。基于模型的软件测试是软件编码阶段的主要测试方法之一，具有测试效率高、排除逻辑复杂故障测试效果好等特点。但是误报、漏报和故障机理有待进一步研究。对主要的测试模型进行了分析和分类，同时，对故障密度等参数进行了初步的分析；最后，提出了一种基于模型的软件测试流程。
Abstract:
本文介绍了一个企业信息门户中单点登录系统的设计与实现。系统实现了一个基于Java EE架构的结合凭证加密和Web Services的单点登录系统，对门户用户进行统一认证和访问控制。论文详细阐述了该系统的总体结构、设计思想、工作原理和具体实现方案，目前系统已在部分省市的广电行业信息门户平台中得到了良好的应用。
本文介绍了一个企业信息门户中单点登录系统的设计与实现。系统实现了一个基于Java EE架构的结合凭证加密和Web Services的单点登录系统，对门户用户进行统一认证和访问控制。论文详细阐述了该系统的总体结构、设计思想、工作原理和具体实现方案，目前系统已在部分省市的广电行业信息门户平台中得到了良好的应用。
Abstract:
排序是计算机程序设计中一种重要操作，本文论述了C语言中快速排序算法的改进，即快速排序与直接插入排序算法相结合的实现过程。在C语言程序设计中，实现大量的内部排序应用时，所寻求的目的就是找到一个简单、有效、快捷的算法。本文着重阐述快速排序的改进与提高过程，从基本的性能特征到基本的算法改进，通过不断的分析，实验，最后得出最佳的改进算法。
排序是计算机程序设计中一种重要操作，本文论述了C语言中快速排序算法的改进，即快速排序与直接插入排序算法相结合的实现过程。在C语言程序设计中，实现大量的内部排序应用时，所寻求的目的就是找到一个简单、有效、快捷的算法。本文着重阐述快速排序的改进与提高过程，从基本的性能特征到基本的算法改进，通过不断的分析，实验，最后得出最佳的改进算法。
Abstract:
综合考虑基于构件组装技术的虚拟实验室的系统需求，分析了工作流驱动的动态虚拟实验室的业务处理模型，介绍了轻量级J2EE框架(SSH)与工作流系统(Shark和JaWE)的集成模型，提出了一种轻量级J2EE框架下工作流驱动的动态虚拟实验室的设计和实现方法，给出了虚拟实验项目的实现机制、数据流和控制流的管理方法，以及实验流程的动态组装方法，最后，以应用实例说明了本文方法的有效性。
综合考虑基于构件组装技术的虚拟实验室的系统需求，分析了工作流驱动的动态虚拟实验室的业务处理模型，介绍了轻量级J2EE框架(SSH)与工作流系统(Shark和JaWE)的集成模型，提出了一种轻量级J2EE框架下工作流驱动的动态虚拟实验室的设计和实现方法，给出了虚拟实验项目的实现机制、数据流和控制流的管理方法，以及实验流程的动态组装方法，最后，以应用实例说明了本文方法的有效性。
Abstract:
本文介绍了Visual C++6.0在对话框的多个文本框之间,通过回车键转移焦点的几种方法,并提出了一个改进方法.
本文介绍了Visual C++6.0在对话框的多个文本框之间,通过回车键转移焦点的几种方法,并提出了一个改进方法.
Abstract:
DICOM 是医学图像存储和传输的国际标准，DCMTK 是免费开源的针对DICOM 标准的开发包。解读DICOM 文件格式并解决DICOM 医学图像显示问题是医学图像处理的基础，对医学影像技术的研究具有重要意义。解读了DICOM 文件格式并介绍了调窗处理的原理，利用VC++和DCMTK 实现医学图像显示和调窗功能。
DICOM 是医学图像存储和传输的国际标准，DCMTK 是免费开源的针对DICOM 标准的开发包。解读DICOM 文件格式并解决DICOM 医学图像显示问题是医学图像处理的基础，对医学影像技术的研究具有重要意义。解读了DICOM 文件格式并介绍了调窗处理的原理，利用VC++和DCMTK 实现医学图像显示和调窗功能。
Abstract:
介绍了一种基于DWGDirectX在不依赖于AutoCAD平台的情况下实现DWG文件的显示、操作、添加的简单的实体的方法，并对该方法进行了分析和实现。
介绍了一种基于DWGDirectX在不依赖于AutoCAD平台的情况下实现DWG文件的显示、操作、添加的简单的实体的方法，并对该方法进行了分析和实现。
Abstract:
本文介绍了一种将DTD转换成ER图,并用XMLApplication将ER图描述成转换标准,然后根据该转换标准将XML文档转换为关系模型的方法.
本文介绍了一种将DTD转换成ER图,并用XMLApplication将ER图描述成转换标准,然后根据该转换标准将XML文档转换为关系模型的方法.
Abstract:
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论文对HDF数据格式和函数库进行研究,重点以栅格图像为例,详细论述如何利用VC++.net和VC#.net对光栅数据进行读取与处理,然后根据所得到的象素矩阵用描点法显示图像.论文是以国家气象中心开发Micaps3.0(气象信息综合分析处理系统)的课题研究为背景的.
论文对HDF数据格式和函数库进行研究,重点以栅格图像为例,详细论述如何利用VC++.net和VC#.net对光栅数据进行读取与处理,然后根据所得到的象素矩阵用描点法显示图像.论文是以国家气象中心开发Micaps3.0(气象信息综合分析处理系统)的课题研究为背景的.
Abstract:
本文介绍非实时操作系统Windows 2000下,利用VisualC++6.0开发实时数据采集的方法.所用到的数据采集卡是研华的PCL-818L.借助数据采集卡PCL-818L的DLLs中的API函数,提出三种实现高速实时数据采集的方法及优缺点.
本文介绍非实时操作系统Windows 2000下,利用VisualC++6.0开发实时数据采集的方法.所用到的数据采集卡是研华的PCL-818L.借助数据采集卡PCL-818L的DLLs中的API函数,提出三种实现高速实时数据采集的方法及优缺点.
Abstract:
排序是计算机程序设计中一种重要操作，本文论述了C语言中快速排序算法的改进，即快速排序与直接插入排序算法相结合的实现过程。在C语言程序设计中，实现大量的内部排序应用时，所寻求的目的就是找到一个简单、有效、快捷的算法。本文着重阐述快速排序的改进与提高过程，从基本的性能特征到基本的算法改进，通过不断的分析，实验，最后得出最佳的改进算法。
排序是计算机程序设计中一种重要操作，本文论述了C语言中快速排序算法的改进，即快速排序与直接插入排序算法相结合的实现过程。在C语言程序设计中，实现大量的内部排序应用时，所寻求的目的就是找到一个简单、有效、快捷的算法。本文着重阐述快速排序的改进与提高过程，从基本的性能特征到基本的算法改进，通过不断的分析，实验，最后得出最佳的改进算法。
Abstract:
随着Internet的迅速发展，网络资源越来越丰富，人们如何从网络上抽取信息也变得至关重要，尤其是占网络资源80%的Deep Web信息检索更是人们应该倍加关注的难点问题。为了更好的研究Deep Web爬虫技术，本文对有关Deep Web爬虫的内容进行了全面、详细地介绍。首先对Deep Web爬虫的定义及研究目标进行了阐述，接着介绍了近年来国内外关于Deep Web爬虫的研究进展，并对其加以分析。在此基础上展望了Deep Web爬虫的研究趋势，为下一步的研究奠定了基础。
随着Internet的迅速发展，网络资源越来越丰富，人们如何从网络上抽取信息也变得至关重要，尤其是占网络资源80%的Deep Web信息检索更是人们应该倍加关注的难点问题。为了更好的研究Deep Web爬虫技术，本文对有关Deep Web爬虫的内容进行了全面、详细地介绍。首先对Deep Web爬虫的定义及研究目标进行了阐述，接着介绍了近年来国内外关于Deep Web爬虫的研究进展，并对其加以分析。在此基础上展望了Deep Web爬虫的研究趋势，为下一步的研究奠定了基础。
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Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address：4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code：100190
Phone：010-62661041 Fax： Email：csa (a) iscas.ac.cn
Technical Support：Beijing Qinyun Technology Development Co., Ltd.
